code: def __init__(self, dht, in_features, num_classes, num_experts):
      super().__init__()
      self.moe = RemoteSwitchMixtureOfExperts(
          in_features=in_features,
          grid_size=(num_experts,),
          dht=dht,
          jitter_eps=0,
          uid_prefix="expert.",
          k_best=1,
          k_min=1,
      )
      self.linear = nn.Linear(in_features, num_classes)
  
file_path: hivemind/tests/test_training.py
imports: from functools import partial
  import pytest
  import torch
  import torch.nn
  import torch.nn.functional
  from sklearn.datasets import load_digits
  from hivemind import DHT
  from hivemind.moe.client import RemoteMixtureOfExperts, RemoteSwitchMixtureOfExperts
  from hivemind.moe.client.expert import create_remote_experts
  from hivemind.moe.expert_uid import ExpertInfo
  from hivemind.moe.server import background_server
label_desc: Use image node_id 1 to create a new SwitchNetwork object from inherited base classes: nn with example: obj = SwitchNetwork(dht, in_features, num_classes, num_experts)